Abstract - Video and image processing is a form of signal processing where the input is an image, such as photographs or frames of video, and the output can be either an image or a set of characteristics or parameters related to the image. When a device such as a camera or scanner captures an image, the device sometimes adds extraneous noise to the image, or the noise may be added to the video or image during the transmission process from source to destination, this. Some types of noise can be simply removed, but most noise requires more involved filtering. this paper will compare reduction of noise from video using Finite impulse response filter and median filter in spatial domain.
, (10-2009)

Abstract Modified extend least-squares parameter estimation algorithm is derived for the special case of ARMAX model identification algorithm. In this method, identification algorithm transform into two sub problems with smaller sizes is used. System identification model and noise identification model. The proposed algorithm has high computational efficiency because the dimensions of its covariance matrices become small. Also, residual generation and evaluation are computed. In simulation, the estimation error of standard recursive least algorithm and two stage extended least squares algorithm are calculated and plotted. The figure shows effectiveness of the proposed algorithm. Next, parameter is estimated using of modified extended least squares algorithm to show the accuracy of the method. Finally, residual is generated and threshold is designed to detect the fault. The figures indicate that the proposed algorithm is sensitive to the faults.
, , , , (4-2017)

Abstract Modified extend least-squares parameter estimation algorithm is derived for the special case of ARMAX model identification algorithm. In this method, identification algorithm transform into two sub problems with smaller sizes is used. System identification model and noise identification model. The proposed algorithm has high computational efficiency because the dimensions of its covariance matrices become small. Also, residual generation and evaluation are computed. In simulation, the estimation error of standard recursive least algorithm and two stage extended least squares algorithm are calculated and plotted. The figure shows effectiveness of the proposed algorithm. Next, parameter is estimated using of modified extended least squares algorithm to show the accuracy of the method. Finally, residual is generated and threshold is designed to detect the fault. The figures indicate that the proposed algorithm is sensitive to the faults.
, , , , (4-2017)